filters.eigenvalues¶
The eignvalue filter returns the eigenvalues for a given point, based on its k-nearest neighbors.
The filter produces three new dimensions (Eigenvalue0
, Eigenvalue1
, and
Eigenvalue2
), which can be analyzed directly, or consumed by downstream
stages for more advanced filtering. The eigenvalues are sorted in ascending
order.
The eigenvalue decomposition is performed using Eigen’s SelfAdjointEigenSolver.
Example¶
This pipeline demonstrates the calculation of the eigenvalues. The newly created dimensions are written out to BPF for further inspection.
[
"input.las",
{
"type":"filters.eigenvalues",
"knn":8
},
{
"type":"writers.bpf",
"filename":"output.bpf",
"output_dims":"X,Y,Z,Eigenvalue0,Eigenvalue1,Eigenvalue2"
}
]
Options¶
- knn
The number of k-nearest neighbors. [Default: 8]
- normalize
Normalize eigenvalues such that the sum is 1. [Default: false]